Genome-wide gene expression noise in Escherichia coli is condition-dependent and determined by propagation of noise through the regulatory network

Although it is well appreciated that gene expression is inherently noisy and that transcriptional noise is encoded in a promoter’s sequence, little is known about the extent to which noise levels of individual promoters vary across growth conditions. Using flow cytometry, we here quantify transcriptional noise in Escherichia coli genome-wide across 8 growth conditions and find that noise levels systematically decrease with growth rate, with a condition-dependent lower bound on noise. Whereas constitutive promoters consistently exhibit low noise in all conditions, regulated promoters are both more noisy on average and more variable in noise across conditions. Moreover, individual promoters show highly distinct variation in noise across conditions. We show that a simple model of noise propagation from regulators to their targets can explain a significant fraction of the variation in relative noise levels and identifies TFs that most contribute to both condition-specific and condition-independent noise propagation. In addition, analysis of the genome-wide correlation structure of various gene properties shows that gene regulation, expression noise, and noise plasticity are all positively correlated genome-wide and vary independently of variations in absolute expression, codon bias, and evolutionary rate. Together, our results show that while absolute expression noise tends to decrease with growth rate, relative noise levels of genes are highly condition-dependent and determined by the propagation of noise through the gene regulatory network.

Independent control of mean and noise by convolution of gene expression distributions

Gene expression noise can reduce cellular fitness or facilitate processes such as alternative metabolism, antibiotic resistance, and differentiation. Unfortunately, efforts to study the impacts of noise have been hampered by a scaling relationship between noise and expression level from individual promoters. Here, we use theory to demonstrate that mean and noise can be controlled independently by expressing two copies of a gene from separate inducible promoters in the same cell. We engineer low and high noise inducible promoters to validate this result in Escherichia coli, and develop a model that predicts the experimental distributions. Finally, we use our method to reveal that the response of a promoter to a repressor is less sensitive with higher repressor noise and explain this result using a law from probability theory. Our approach can be applied to investigate the effects of noise on diverse biological pathways or program cellular heterogeneity for synthetic biology applications.

A high-density lineage tree reveals dynamics of expression differences accumulation in nondifferentiating clonal expansion

Differences in gene expression levels among genetically identical cells naturally accumulate during cellular proliferation, forming the basis of expression noise or differentiation. Nevertheless, how transcriptome-wide noise accumulation is constrained to maintain homeostasis during continuous cell divisions has remained largely unresolved. We developed a novel method named single-cell transcriptome and dense tree (STADT) to simultaneously determines the transcriptomes and lineage tree of >50% single cells in a single-cell-seeded colony. This lineage tree revealed gradual accumulation of transcriptome differences that became saturated upon four cell divisions, reduced expression noise for sub-tree/sub-colonies closer to inferred expression boundaries, and transcriptionally modulated co-fluctuations among genes. These results collectively showed, for the first time, constrained dynamics of expression noise in the context of cell division.

Double-edged role of resource competition in gene expression noise and control

Despite extensive investigation demonstrating that resource competition can significantly alter the circuits' deterministic behaviors, a fundamental issue is how resource competition contributes to the gene expression noise and how the noise can be controlled. Utilizing a two-gene circuit as a prototypical system, we uncover a surprising double-edged role of resource competition in gene expression noise: the competition decreases noise through a resource constraint but generates its own type of noise which we name as ''resource competitive noise.'' Utilization of orthogonal resources enables retaining the noise reduction conferred by resource constraint while removing the added resource competitive noise. The noise reduction effects are studied using three negative feedback controller types: negatively competitive regulation (NCR), local, and global controllers, each having four placement architectures in the protein biosynthesis pathway (mRNA or protein inhibition on transcription or translation). Our results show that both local and NCR controllers with mRNA-mediated inhibition are efficacious at reducing noise, with NCR controllers demonstrating a superior noise-reduction capability. We also find that combining negative feedback controllers with orthogonal resources can improve the local controllers. This work provides deep insights into the origin of stochasticity in gene circuits with resource competition and guidance for developing effective noise control strategies.

Reduction in gene expression noise by targeted increase in accessibility at gene loci

Many eukaryotic genes are expressed in randomly initiated bursts that are punctuated by periods of quiescence. Here, we show that the intermittent access of the promoters to transcription factors through relatively impervious chromatin contributes to this “noisy” transcription. We tethered a nuclease-deficient Cas9 fused to a histone acetyl transferase at the promoters of two endogenous genes in HeLa cells. An assay for transposase-accessible chromatin using sequencing showed that the activity of the histone acetyl transferase altered the chromatin architecture locally without introducing global changes in the nucleus and rendered the targeted promoters constitutively accessible. We measured the gene expression variability from the gene loci by performing single-molecule fluorescence in situ hybridization against mature messenger RNAs (mRNAs) and by imaging nascent mRNA molecules present at active gene loci in single cells. Because of the increased accessibility of the promoter to transcription factors, the transcription from two genes became less noisy, even when the average levels of expression did not change. In addition to providing evidence for chromatin accessibility as a determinant of the noise in gene expression, our study offers a mechanism for controlling gene expression noise which is otherwise unavoidable.

Cis-Regulatory Logic Produces Gene-Expression Noise Describing Phenotypic Heterogeneity in Bacteria

Gene transcriptional process is random. It occurs in bursts and follows single-molecular kinetics. Intermittent bursts are measured based on their frequency and size. They influence temporal fluctuations in the abundance of total mRNA and proteins by generating distinct transcriptional variations referred to as “noise”. Noisy expression induces uncertainty because the association between transcriptional variation and the extent of gene expression fluctuation is ambiguous. The promoter architecture and remote interference of different cis-regulatory elements are the crucial determinants of noise, which is reflected in phenotypic heterogeneity. An alternative perspective considers that cellular parameters dictating genome-wide transcriptional kinetics follow a universal pattern. Research on noise and systematic perturbations of promoter sequences reinforces that both gene-specific and genome-wide regulation occur across species ranging from bacteria and yeast to animal cells. Thus, deciphering gene-expression noise is essential across different genomics applications. Amidst the mounting conflict, it is imperative to reconsider the scope, progression, and rational construction of diversified viewpoints underlying the origin of the noise. Here, we have established an indication connecting noise, gene expression variations, and bacterial phenotypic variability. This review will enhance the understanding of gene-expression noise in various scientific contexts and applications.

An emerging and variant viral promoter of HIV-1 subtype C exhibits low-level gene expression noise

Background We observe the emergence of several promoter-variant viral strains in India during recent years. The variant viral promoters contain additional copies of transcription factor binding sites present in the viral modulatory region or enhancer, including RBEIII, LEF-1, Ap-1 and/or NF-κB. These sites are crucial for governing viral gene expression and latency. Here, we infer that one variant viral promoter R2N3-LTR containing two copies of RBF-2 binding sites (an RBEIII site duplication) and three copies of NF-κB motifs may demonstrate low levels of gene expression noise as compared to the canonical RN3-LTR or a different variant R2N4-LTR (a duplication of an RBEIII site and an NF-κB motif). To demonstrate this, we constructed a panel of sub-genomic viral vectors of promoter-variant LTRs co-expressing two reporter proteins (mScarlet and Gaussia luciferase) under the dual-control of Tat and Rev. We established stable pools of CEM.NKR-CCR5 cells (CEM-CCR5RL reporter cells) and evaluated reporter gene expression under different conditions of cell activation. Results The R2N3-LTR established stringent latency that was highly resistant to reversal by potent cell activators such as TNF-α or PMA, or even to a cocktail of activators, compared to the canonical RN3- or the variant R2N4-LTR. The R2N3-LTR exhibited low-level basal gene expression in the absence of cell activation that enhanced marginally but significantly when activated. In the presence of Tat and Rev, trans-complemented in the form of an infectious virus, the R2N3-LTR demonstrated gene expression at levels comparable to the wild-type viral promoter. The R2N3-LTR is responsive to Tat and Rev factors derived from viral strains representing diverse genetic subtypes. Conclusion With extremely low-level transcriptional noise, the R2N3-LTR can serve as an excellent model to examine the establishment, maintenance, and reversal of HIV-1 latency. The R2N3-LTR would also be an ideal viral promoter to develop high-throughput screening assays to identify potent latency-reversing agents since the LTR is not affected by the usual background noise of the cell.

A DNA-repair pathway can affect transcriptional noise to promote cell fate transitions

Stochastic fluctuations in gene expression (‘noise’) are often considered detrimental, but fluctuations can also be exploited for benefit (e.g., dither). We show here that DNA base-excision repair amplifies transcriptional noise to facilitate cellular reprogramming. Specifically, the DNA-repair protein Apex1, which recognizes both naturally occurring and unnatural base modifications, amplifies expression noise while homeostatically maintaining mean-expression levels. This amplified expression noise originates from shorter duration, higher intensity, transcriptional bursts generated by Apex1-mediated DNA supercoiling. The remodeling of DNA topology first impedes and then accelerates transcription to maintain mean levels. This mechanism, which we term Discordant Transcription through Repair (DiThR; pronounced /’dither’/), potentiates cellular reprogramming and differentiation. Our study reveals a potential functional role for transcriptional fluctuations mediated by DNA base modifications in embryonic development and disease.